As discussed in Color, for each displayed/printed pixel of a color image, the dataset/image has three or four values. To store/show the three values for each pixel, cameras and monitors allocate a certain fraction of each pixel’s area to red, green and blue filters. These three filters are thus built into the hardware at the pixel level.
However, because measurement accuracy is very important in scientific instruments, and we want to do measurements (take images) with various/custom filters (without having to order a new expensive detector!), scientific detectors use the full area of the pixel to store one value for it in a single/mono channel dataset. To make measurements in different filters, we just place a filter in the light path before the detector. Therefore, the FITS format that is used to store astronomical datasets is inherently a mono-channel format (see Recognized file formats or Fits).
When a subject has been imaged in multiple filters, you can feed each different filter into the red, green and blue channels of your monitor and obtain a false-colored visualization. The reason we say “false-color” (or pseudo color) is that generally, the three data channels you provide are not from the same Red, Green and Blue filters of your monitor! So the observed color on your monitor does not correspond the physical “color” that you would have seen if you looked at the object by eye. Nevertheless, it is good (and sometimes necessary) for visualization (of special features).
In ConvertType, you can do this by giving each separate single-channel dataset (for example, in the FITS image format) as an argument (in the proper order), then asking for the output in a format that supports multi-channel datasets (for example, see the command below, or ConvertType input and output).
$ astconvertt r.fits g.fits b.fits --output=color.jpg